create a column based on datetime column condition R

I have the following data example:

structure(list(datetime = structure(c(1662185434.08, 1662185435.075, 
1662185436.074, 1662185437.07, 1662185439.067, 1662185439.067, 
1662185442.069, 1662185444.071, 1662185445.077, 1662207092.793, 
1662207093.998, 1662207097.023, 1662207099.025, 1662207100.019, 
1662207101.018, 1662207101.018, 1662207101.018, 1662207102.02, 
1662207102.02, 1662207107.007, 1662207109.007), tzone = "UTC", class = c("POSIXct", 
"POSIXt"))), row.names = c(NA, -21L), class = c("data.table", 
"data.frame"))

I would like to create a column cycle, that compare a lrow of a datetime and the row above, if this were a time difference greater that 5 minutes the name in cycle will to be cycle_2, the next difference greater than 5 minutes will be cycle 3 and so on. As the example below.

structure(list(datetime = structure(c(1662185434.08, 1662185435.075, 
1662185436.074, 1662185437.07, 1662185439.067, 1662185439.067, 
1662185442.069, 1662185444.071, 1662185445.077, 1662207092.793, 
1662207093.998, 1662207097.023, 1662207099.025, 1662207100.019, 
1662207101.018, 1662207101.018, 1662207101.018, 1662207102.02, 
1662207102.02, 1662207107.007, 1662207109.007), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), diff_min = c(0.0165833353996277, 0.0166499972343445, 
0.0166000048319499, 0.0332833290100098, 0, 0.0500333348910014, 
0.0333666682243347, 0.0167666673660278, 360.795266664028, 0.0200833360354106, 
0.0504166642824809, 0.0333666682243347, 0.0165666659673055, 0.0166500012079875, 
0, 0, 0.0166999975840251, 0, 0.0831166664759318, 0.0333333333333333, 
0), cycle = c("ciclo_1", "ciclo_1", "ciclo_1", "ciclo_1", "ciclo_1", 
"ciclo_1", "ciclo_1", "ciclo_1", "ciclo_2", "ciclo_2", "ciclo_2", 
"ciclo_2", "ciclo_2", "ciclo_2", "ciclo_2", "ciclo_2", "ciclo_2", 
"ciclo_2", "ciclo_2", "ciclo_2", "ciclo_2")), row.names = c(NA, 
-21L), class = c("data.table", "data.frame"))

My code at the moment is:

df %>%
arrange(datetime) %>% 
mutate(diff_min = as.numeric(lead(datetime) - datetime) / 60, cycle = ifelse(diff_min < 5, "ciclo_1", paste0("ciclo_", cumsum(diff_min >= 5) + 1)))

Thanks any help

We can use cumsum here:

library(dplyr)
quux %>%
  arrange(datetime) %>%
  mutate(
    diff_min = c(as.numeric(diff(datetime), units = "mins"), 0),
    cycle = 1+cumsum(diff_min > 5)
  )
#               datetime     diff_min cycle
# 1  2022-09-03 06:10:34   0.01658334     1
# 2  2022-09-03 06:10:35   0.01665000     1
# 3  2022-09-03 06:10:36   0.01660000     1
# 4  2022-09-03 06:10:37   0.03328333     1
# 5  2022-09-03 06:10:39   0.00000000     1
# 6  2022-09-03 06:10:39   0.05003333     1
# 7  2022-09-03 06:10:42   0.03336667     1
# 8  2022-09-03 06:10:44   0.01676666     1
# 9  2022-09-03 06:10:45 360.79526667     2
# 10 2022-09-03 12:11:32   0.02008333     2
# 11 2022-09-03 12:11:33   0.05041667     2
# 12 2022-09-03 12:11:37   0.03336667     2
# 13 2022-09-03 12:11:39   0.01656667     2
# 14 2022-09-03 12:11:40   0.01665000     2
# 15 2022-09-03 12:11:41   0.00000000     2
# 16 2022-09-03 12:11:41   0.00000000     2
# 17 2022-09-03 12:11:41   0.01670000     2
# 18 2022-09-03 12:11:42   0.00000000     2
# 19 2022-09-03 12:11:42   0.08311667     2
# 20 2022-09-03 12:11:47   0.03333333     2
# 21 2022-09-03 12:11:49   0.00000000     2

to which you can paste0("ciclo_", cycle) if you'd like.

Since your data is originally class "data.table", here's an alternative:

library(data.table)
quux[, cycle := cumsum(c(TRUE, as.numeric(diff(datetime), units = "mins") >= 5))]

without the intermediate diff_min, in case you don't need that variable for anything else.

Data

quux <- data.table::as.data.table(structure(list(datetime = structure(c(1662185434.08, 1662185435.075, 1662185436.074, 1662185437.07, 1662185439.067, 1662185439.067, 1662185442.069, 1662185444.071, 1662185445.077, 1662207092.793, 1662207093.998, 1662207097.023, 1662207099.025, 1662207100.019, 1662207101.018, 1662207101.018, 1662207101.018, 1662207102.02, 1662207102.02, 1662207107.007, 1662207109.007), tzone = "UTC", class = c("POSIXct", "POSIXt"))), row.names = c(NA, -21L), class = c("data.table", "data.frame")))